Quantitative Model Analyst (Multiple openings) in Charlotte, NC

U.S. Bank•Charlotte, NC

1d•$78,270 - $123,000

About The Position

U.S. Bank is seeking a full-time Quantitative Model Analyst (Multiple openings) in Charlotte, NC. The Quantitative Model Analyst develops mathematical and complex statistical models for use in sound management of the bank’s portfolio as well as regulatory requirements. The models are used in the Treasury department to measure interest rate risk (IRR), valuation of market value of equity (MVE) analysis, net interest income (NII) analysis, Comprehensive Capital Analysis and Review (CCAR) regulatory exercise, and Business As Usual (BAU) activities. This role is responsible for developing models that adhere to internal development standards and templates for model governance, and to model risk policies and bank Supervision and Regulation Letters including SR 11-, SR 15-18, and SR 15-19. Specific duties include: (1) researching market and idiosyncratic drivers germane to the portfolio and intended use case; (2) creating model development and validation documentation including: presentations, written reports, model or reporting code documentation, business requirements, monitoring reports and related code, and procedures; (3) compiling and analyzing complex datasets using programming and quantitative analysis to support data-driven decision making; (4) developing quantitative financial strategies for business development; (5) compiling and analyzing complex datasets using programming and quantitative analysis to support data-driven decision making; (6) solving quantitative financial challenges through model research, development and validation; (7) implementing various regression techniques, parametric and non-parametric algorithms, times series techniques, model validation tests/methodologies, using SAS and Python; (8) implementing various regression and other financial modeling techniques, parametric and non-parametric algorithms, times series techniques, model validation tests/methodologies, using SAS and Python; and (9) communicating models and subsequent impacts to the Treasury department as well as business units outside of Treasury.

Requirements

This position requires a Master’s degree or equivalent in Financial Mathematics, or related quantitative field and 3 years of experience working with complex statistical models.
In the alternative, will accept a Bachelor’s degree or equivalent in Financial Mathematics, or related quantitative field and 5 years (progressive, post-baccalaureate) of experience working with complex statistical models.
Must also have 24 months of experience with each of the following: (1) developing quantitative financial strategies for business development; (2) compiling and analyzing complex datasets using programming and quantitative analysis to support data-driven decision making; (3) solving quantitative financial challenges through model research, development and validation; (4) creating model development and validation documentation including: presentations, written reports, model or reporting code documentation, business requirements, monitoring reports and related code, and procedures; and (5) implementing various regression techniques, parametric and non-parametric algorithms, times series techniques, model validation tests/methodologies, using SAS and Python.

Responsibilities

researching market and idiosyncratic drivers germane to the portfolio and intended use case
creating model development and validation documentation including: presentations, written reports, model or reporting code documentation, business requirements, monitoring reports and related code, and procedures
compiling and analyzing complex datasets using programming and quantitative analysis to support data-driven decision making
developing quantitative financial strategies for business development
compiling and analyzing complex datasets using programming and quantitative analysis to support data-driven decision making
solving quantitative financial challenges through model research, development and validation
implementing various regression techniques, parametric and non-parametric algorithms, times series techniques, model validation tests/methodologies, using SAS and Python
implementing various regression and other financial modeling techniques, parametric and non-parametric algorithms, times series techniques, model validation tests/methodologies, using SAS and Python
communicating models and subsequent impacts to the Treasury department as well as business units outside of Treasury

Benefits

Healthcare (medical, dental, vision)
Basic term and optional term life insurance
Short-term and long-term disability
Pregnancy disability and parental leave
401(k) and employer-funded retirement plan
Paid vacation (from two to five weeks depending on salary grade and tenure)
Up to 11 paid holiday opportunities
Adoption assistance
Sick and Safe Leave accruals of one hour for every 30 worked, up to 80 hours per calendar year unless otherwise provided by law
incentive and recognition programs
equity stock purchase
401(k) contribution and pension (all benefits are subject to eligibility requirements)